This document provides an overview of a hands-on tutorial on using the GoodRelations ontology, RDFa, and Yahoo! SearchMonkey to annotate e-commerce data on the Semantic Web. The learning goals are to use GoodRelations and RDFa to augment websites with product details, publish structured data using RDFa, and query the data using SPARQL. The agenda includes introductions, motivations for the Semantic Web, tutorials on GoodRelations and RDFa, exercises annotating a web shop, and demonstrations of querying and publishing semantic data.

1. The Web of Data for E-Commerce in Brief
A Hands-on Introduction to the GoodRelations Ontology,
RDFa, and Yahoo! SearchMonkey
October 25, 2009
Westfields Conference Center near Washington, DC, USA
Martin Hepp
Universität der Bundeswehr München, Munich, Germany
Richard Cyganiak
Digital Enterprise Research Institute (DERI), Ireland

2. About the Organizers
Martin Hepp Richard Cyganiak
Professor, Head of Group PhD Researcher
Universität der Bundeswehr München Digital Enterprise Research Institute
Munich, Germany (DERI), Galway, Ireland
mhepp@computer.org richard.cyganiak@deri.org
http://www.heppnetz.de http://www.deri.ie
Previous affiliations: Universität Previous affiliations: FU Berlin,
Würzburg (Germany), Florida Gulf Germany
Coast University, IBM Zurich
Research Lab, DERI/STI
Innsbruck
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3. Learning Goals
Participants will learn
• to use
– the GoodRelations conceptual structures and
– the RDFa syntax
to augment static and dynamic Web sites by the various relevant
details of a commercial Web presence;
• RDFa modeling patterns for more complex RDF structures;
• to publish data on the Semantic Web and make it available for
indexing services, repositories, Yahoo SearchMonkey and
applications;
• to query the Web of Data using SPARQL, and
• the development of simple Yahoo SearchMonkey and Yahoo
BOSS applications.
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4. Logistics
08:30-10:30 Overview and Motivation: Why the Web of Data is Now 30’
Quick Review of Prerequisites 15’
The GoodRelations Ontology: E-Commerce on the Web of Data 75’
10:30-10:45 Coffee Break
10:45-12:30 RDFa: Bridging the Web of Documents with the Web of Data 45’
Expressing GoodRelations in RDFa: A Running Example 30’
GoodRelations – Advanced Topics 30’
12:30-13:30 Lunch Break
13:30-16:00 Hands-on Exercise: Annotating a Web Shop 60’
Querying the Web of Data for Offerings – SPARQL 15’
Querying the Web of Data – Exercises 15’
16:00-16:30 Coffee Break
16:30-18:00 Publishing Semantic Web Data: Make Your RDF Available 30’
Yahoo SearchMonkey and Yahoo BOSS 45’
Discussion, Conclusion, Feedback Round 15’
4

5. Resources: Information
• Wiki page
http://tr.im/srGx
http://www.ebusiness-unibw.org/wiki/Web_of_Data_for_E-Commerce_Tutorial_ISWC2009
• GoodRelations Primer
http://www.heppnetz.de/projects/goodrelations/primer/
• GoodRelations Documentation
http://purl.org/goodrelations/v1
• RDFa
http://www.w3.org/TR/2008/REC-rdfa-syntax-20081014/
• SPARQL
http://www.w3.org/TR/rdf-sparql-query/
• Yahoo SearchMonkey
http://developer.yahoo.com/searchmonkey/smguide/
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6. Resources: Tools
• RDF Validator (and Visualizer)
http://www.w3.org/RDF/Validator/
• GoodRelations Annotator
http://www.ebusiness-unibw.org/tools/goodrelations-annotator/
• PyRDFa
http://www.w3.org/2007/08/pyRdfa/
• Twinkle
http://www.ldodds.com/projects/twinkle/
Custom configuration file from Wiki
• RDF2dataRSS
http://www.ebusiness-unibw.org/tools/rdf2datarss/
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7. Overview and Motivation: Why the
Web of Data is Now
Martin Hepp
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8. Limitations of the Web, 2009

9. Specificity vs. Keyword-based Search
• Synonyms
• Homonyms
• Multiple languages
• No parametric
search
9

10. No Unified View: Jumping Back and Forth
Across Data Silos
Site Page Page
Search Engine Results
Search Engine Results
1 1 2
Search Engine Results
Search Engine Results
Page Page
3 4
Site Page
2 5
Site Page Page Page
3 6 7 8
10

11. We know the best hits only when done.
Site Page Page
1 1 2
Search Engine Results
Page Page
3 4
Site Page
2 5
Site Page Page Page
3 6 7 8
11

12. Limited Ability to Reuse Data
12

13. The Web: A Bottleneck for Sharing
Product Data
13

14. Web of Data (“Semantic Web”)
14

15. E-Commerce on the Web of Data
15

16. Goal: A Unified View on Commerce
Data on the Web
Extraction
Arbitrary Query and Reuse
Manufacturers
Retailers
Payment
Delivery
Product Model Warranty
Master Data Shop Spare Parts &
Offerings Auctions Consumables
16

17. On the Shoulders of Giants
A Unified View of Commerce Data
on the Web
17
Martin Hepp,
mhepp@compu

18. Deep Comparison Shopping
Search Engine Results
Site
Site
Site
3
1
2
Page
Page
Page
6
5
1
Page
Page
7
3
Page
2
Page
Page
8
4
18
Martin Hepp,
mhepp@compu

19. Use Case 1: Product Search
• Find all MP3 players
that have a USB
interface and a color
display, and sort them
by weight (lightest
first).
...on a Web Scale!
19

20. Use Case 2: Product Model Data Reuse
World Wide Web
World Wide Web
Manufacturer Retailer /
Web Shop
Structured
Structured
Data on
Data on
Products
Products and Product Specifications: and
Services
Type of Product, Features etc. Services
20

21. Use Case 3: Fine-grained Affiliate
Marketing
Offers of
computer
add-ons
that have
an USB
interface
Screenshot from http://en.wikipedia.org/wiki/USB
21

22. The Web of Linked Data, Essentially:
1. Cluster Web links by what they mean
2. Use URIs to indicate the type of links
3. Use HTTP URIs so that it is quick and easy to explore
what this URI means.
4. Make clear whether you are referring to something or
its representation.
22
Martin Hepp,
mhepp@compu

23. The Web of Linked Data, Essentially:
1. Cluster Web links by what they mean
2. Use URIs to indicate the type of links
3. Use HTTP URIs so that it is quick and easy to explore
what this URI means.
4. Make clear whether you are referring to something or
its representation.
23
Martin Hepp,
mhepp@compu

24. The Web of Linked Data, Essentially:
1. Cluster Web links by what they mean
2. Use URIs to indicate the type of links
3. Use HTTP URIs so that it is quick and easy to explore
what this URI means.
4. Make clear whether you are referring to something or
its representation.
24
Martin Hepp,
mhepp@compu

25. Technical Effects & Working Assumption
• This will reduce the
computational
complexity of
processing,
combining, reusing
data on a Web scale
25
Martin Hepp,
mhepp@compu

26. Both Sides Can Help Build a Bridge
26
Martin Hepp,
mhepp@compu

27. The Web of Linked Data is NOW and HERE
• RDFa has become a W3C Recommendation
– HTML5+RDFa Specification well underway, too
• Yahoo SearchMonkey and BOSS
• Google adopts RDFa
• GoodRelations ontology
• SPARQL Query language and endpoint interface
• Scalable, commercial repositories
• Linked Data Guidelines: Best Practices for co-
existence of the Web of Data and existing Web content
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28. NOW and HERE: Yahoo & GoodRelations
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29. NOW and HERE: Google (Mock-up)
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30. NOW and HERE: OpenLink Virtuoso Spongers
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31. GoodRelations #2 of all Web Ontologies
…and this does not yet include the > 10 Mio. offers
from Amazon and eBay!
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32. GoodRelations #2 of all Web Ontologies
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33. NOW and HERE: BestBuy
• Details on all 1000+ stores in the US using
GoodRelations
– http://stores.bestbuy.com/sitemap.xml
– http://lod.openlinksw.com/sparql
• Full Catalog: >432,000 item descriptions
– http://products.semweb.bestbuy.com/sitemap.xml
– updated on a daily basis
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34. Thank you.
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